Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)-driven diagnosis and treatment.
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| Title: | Interoception, cardiac health, and heart failure: The potential for artificial intelligence (AI)-driven diagnosis and treatment. |
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| Authors: | Singh M; Department of Physiology, School of Medicine, University of Louisville, Louisville, Kentucky, USA.; Center for Predictive Medicine (CPM) for Biodefense and Emerging Infectious Diseases, School of Medicine, University of Louisville, Louisville, Kentucky, USA., Babbarwal A; Department of Epidemiology and Population Health, School of Public Health and Information Sciences (SPHIS), University of Louisville, Louisville, Kentucky, USA., Pushpakumar S; Department of Physiology, School of Medicine, University of Louisville, Louisville, Kentucky, USA., Tyagi SC; Department of Physiology, School of Medicine, University of Louisville, Louisville, Kentucky, USA. |
| Source: | Physiological reports [Physiol Rep] 2025 Jan; Vol. 13 (1), pp. e70146. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society Country of Publication: United States NLM ID: 101607800 Publication Model: Print Cited Medium: Internet ISSN: 2051-817X (Electronic) Linking ISSN: 2051817X NLM ISO Abbreviation: Physiol Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2051-817X |
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| DOI: | 10.14814/phy2.70146 |
